Arquemino Lopes Junior: The growing variety of products, the continuing boom in e-commerce and the increasing complexity of logistics processes require intelligent automation strategies. Companies need to work more efficiently and cost-effectively in order to remain competitive in this environment. Bin picking is the automated hand of intralogistics. It enables companies to remove a wide variety of objects precisely and reliably from chaotic or organized containers. This technology makes it possible to optimize the flow of materials and avoid bottlenecks in the logistics chain.
Arquemino Lopes Junior: The big challenge is to develop gripping systems that can flexibly and reliably grip a variety of different items. A system that can really grasp any object is like searching for the Holy Grail. The variety of product geometries and materials poses an enormous challenge for automated gripping. If the bin-picking process does not run smoothly, it quickly becomes a bottleneck in intralogistics. The risk here is that the material flow comes to a standstill and the overall system loses performance. On the positive side, companies that successfully integrate intelligent bin picking into their processes will take a decisive step forward. They not only optimize their efficiency, but also create the basis for surviving in a market that demands ever faster and more flexible solutions.
Arquemino Lopes Junior: Online retail is certainly one of the biggest drivers of the current challenges in intralogistics. The pandemic has given a massive boost to e-commerce, and although growth has leveled off somewhat since then, the trend remains positive and sustained. This means that the steadily increasing number of orders is also generating significantly higher processing requirements in logistics. This development is accompanied by a growing variety of products, which means that more different product geometries and materials have to be processed in the bin picking process.
Our expectations as consumers also play a decisive role. We expect ordered products to arrive quickly – preferably on the same day. This expectation presents companies with the additional challenge of processing the already high volumes in e-commerce even faster. This is precisely where it becomes very clear that intelligent and automated bin picking is essential to ensure efficiency, speed and reliability.
Arquemino Lopes Junior: From our point of view, three technological developments in particular have proven to be game changers for bin picking: the influence of AI and machine learning, advances in image processing and object recognition, and the use of real-time data. These have significantly improved the precision and flexibility of the systems.
The most important goal is still to calculate the perfect gripping points and to develop the gripping system at the so-called "end of arm" as efficiently as possible. At Festo, we bring all our expertise in pneumatic, electrical and digital automation to bear in finding solutions to reduce errors to a minimum.
With our broad portfolio of gripper technologies, we can cover almost any application. I would particularly like to highlight our Customized Solutions. These are the result of targeted cooperation with our customers in order to develop customized gripper solutions. In our "Grip it" development initiative, we even have a transnational team working together that specializes in the development of special grippers.
Arquemino Lopes Junior: A good example is predictive maintenance. With our innovative Festo AX software, many of our customers process real-time data from their systems and machines and analyze it using artificial intelligence. This reduces downtimes by up to 25% and sustainably increases the efficiency of their production. But we also rely on Festo AX in electrical automation. By analyzing the power consumption of an electric motor, we can see how it has worked throughout the day. Peaks in energy consumption often indicate an increased torque requirement and mechanical problems. With Festo AX, we identify the causes of performance drops at an early stage and prevent potential faults before they become a problem. Real-time data also gives us valuable insights into whether all components have been optimally selected and dimensioned. This increases efficiency, minimizes wear, extends the service life of the systems and reduces operating costs.
Arquemino Lopes Junior: GripperAI is an absolute innovation for bin picking. With this revolutionary software solution, we enable robots and handling systems to grip disordered objects of different shapes and sizes precisely and flexibly – even if they are in a chaotic position. Our solution uses artificial intelligence, in particular machine learning, to adapt autonomously to changing picking tasks and continuously optimize efficiency in the picking process. CAD templates for the camera configuration or time-consuming teaching of the robot are no longer necessary. GripperAI recognizes objects independently and calculates the best gripping points depending on the situation. This makes the solution particularly flexible and significantly reduces manual effort.
In tests, GripperAI achieved a success rate of almost 100% for simple tasks. Even in complex scenarios with disordered objects and chaotic environments, the success rates were similarly high. This shows how dynamically the software can adapt to different requirements.
Set a new benchmark in the efficiency of your intralogistics with innovative artificial intelligence. Festo solutions enable you to grip random objects of different shapes and sizes fully automatically. GripperAI is an innovative software solution from Festo that has been specially developed for bin picking in intralogistics.
Find out moreArquemino Lopes Junior: We are currently using GripperAI in various pilot and research projects to test new functions and applications. In cooperation with logistics companies, we are testing the technology for gripping different parts – from small objects such as USB memory sticks or cans to heavy boxes.
Planned expansions are aimed at further increasing the software's learning ability and adaptability. This also includes the integration of additional sensor and image processing technologies to further optimize the precision and efficiency of the gripping processes. One particular highlight is our FLAIROP research project. Here, we are investigating how grippers can become even more flexible and intelligent through the use of integrated cameras and distributed AI. Our aim is to use training data across all locations without disclosing sensitive company data.
Arquemino Lopes Junior: Make sure you choose a partner with broad automation expertise and an extensive portfolio in gripper technology. This is the only way to develop solutions that meet the specific requirements of the application. Standard solutions often reach their limits, especially in the area of bin picking. The individual requirements and circumstances are so diverse in many areas of application that customized approaches are essential. Your partner should therefore also be prepared to develop individual solutions together with you.
As many machines are often used in different countries, it is essential that the automation partner is also represented worldwide. This not only guarantees the availability of spare parts, but also the smooth operation of the systems.
And probably one of the most important recommendations is to choose a partner whose development activities cross technology boundaries and who offers everything from a single source – be it pneumatic, electrical or digital solutions. Which technology is used always depends on the requirements of the respective application. A partner with expertise in all areas is best placed to help you develop the right automation strategy for your processes.
We would like to thank Arquemino Lopes Junior for the inspiring interview and the comprehensive information on the importance of bin picking in intralogistics. His expertise and many years of experience have given us important insights into how companies can achieve significant increases in efficiency through automated "bin picking".